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Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software devel...

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Autores principales: Lawson, Catherine L., Kryshtafovych, Andriy, Adams, Paul D., Afonine, Pavel V., Baker, Matthew L., Barad, Benjamin A., Bond, Paul, Burnley, Tom, Cao, Renzhi, Cheng, Jianlin, Chojnowski, Grzegorz, Cowtan, Kevin, Dill, Ken A., DiMaio, Frank, Farrell, Daniel P., Fraser, James S., Herzik, Mark A., Hoh, Soon Wen, Hou, Jie, Hung, Li-Wei, Igaev, Maxim, Joseph, Agnel P., Kihara, Daisuke, Kumar, Dilip, Mittal, Sumit, Monastyrskyy, Bohdan, Olek, Mateusz, Palmer, Colin M., Patwardhan, Ardan, Perez, Alberto, Pfab, Jonas, Pintilie, Grigore D., Richardson, Jane S., Rosenthal, Peter B., Sarkar, Daipayan, Schäfer, Luisa U., Schmid, Michael F., Schröder, Gunnar F., Shekhar, Mrinal, Si, Dong, Singharoy, Abishek, Terashi, Genki, Terwilliger, Thomas C., Vaiana, Andrea, Wang, Liguo, Wang, Zhe, Wankowicz, Stephanie A., Williams, Christopher J., Winn, Martyn, Wu, Tianqi, Yu, Xiaodi, Zhang, Kaiming, Berman, Helen M., Chiu, Wah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864804/
https://www.ncbi.nlm.nih.gov/pubmed/33542514
http://dx.doi.org/10.1038/s41592-020-01051-w
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author Lawson, Catherine L.
Kryshtafovych, Andriy
Adams, Paul D.
Afonine, Pavel V.
Baker, Matthew L.
Barad, Benjamin A.
Bond, Paul
Burnley, Tom
Cao, Renzhi
Cheng, Jianlin
Chojnowski, Grzegorz
Cowtan, Kevin
Dill, Ken A.
DiMaio, Frank
Farrell, Daniel P.
Fraser, James S.
Herzik, Mark A.
Hoh, Soon Wen
Hou, Jie
Hung, Li-Wei
Igaev, Maxim
Joseph, Agnel P.
Kihara, Daisuke
Kumar, Dilip
Mittal, Sumit
Monastyrskyy, Bohdan
Olek, Mateusz
Palmer, Colin M.
Patwardhan, Ardan
Perez, Alberto
Pfab, Jonas
Pintilie, Grigore D.
Richardson, Jane S.
Rosenthal, Peter B.
Sarkar, Daipayan
Schäfer, Luisa U.
Schmid, Michael F.
Schröder, Gunnar F.
Shekhar, Mrinal
Si, Dong
Singharoy, Abishek
Terashi, Genki
Terwilliger, Thomas C.
Vaiana, Andrea
Wang, Liguo
Wang, Zhe
Wankowicz, Stephanie A.
Williams, Christopher J.
Winn, Martyn
Wu, Tianqi
Yu, Xiaodi
Zhang, Kaiming
Berman, Helen M.
Chiu, Wah
author_facet Lawson, Catherine L.
Kryshtafovych, Andriy
Adams, Paul D.
Afonine, Pavel V.
Baker, Matthew L.
Barad, Benjamin A.
Bond, Paul
Burnley, Tom
Cao, Renzhi
Cheng, Jianlin
Chojnowski, Grzegorz
Cowtan, Kevin
Dill, Ken A.
DiMaio, Frank
Farrell, Daniel P.
Fraser, James S.
Herzik, Mark A.
Hoh, Soon Wen
Hou, Jie
Hung, Li-Wei
Igaev, Maxim
Joseph, Agnel P.
Kihara, Daisuke
Kumar, Dilip
Mittal, Sumit
Monastyrskyy, Bohdan
Olek, Mateusz
Palmer, Colin M.
Patwardhan, Ardan
Perez, Alberto
Pfab, Jonas
Pintilie, Grigore D.
Richardson, Jane S.
Rosenthal, Peter B.
Sarkar, Daipayan
Schäfer, Luisa U.
Schmid, Michael F.
Schröder, Gunnar F.
Shekhar, Mrinal
Si, Dong
Singharoy, Abishek
Terashi, Genki
Terwilliger, Thomas C.
Vaiana, Andrea
Wang, Liguo
Wang, Zhe
Wankowicz, Stephanie A.
Williams, Christopher J.
Winn, Martyn
Wu, Tianqi
Yu, Xiaodi
Zhang, Kaiming
Berman, Helen M.
Chiu, Wah
author_sort Lawson, Catherine L.
collection PubMed
description This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density.
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spelling pubmed-78648042021-02-08 Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge Lawson, Catherine L. Kryshtafovych, Andriy Adams, Paul D. Afonine, Pavel V. Baker, Matthew L. Barad, Benjamin A. Bond, Paul Burnley, Tom Cao, Renzhi Cheng, Jianlin Chojnowski, Grzegorz Cowtan, Kevin Dill, Ken A. DiMaio, Frank Farrell, Daniel P. Fraser, James S. Herzik, Mark A. Hoh, Soon Wen Hou, Jie Hung, Li-Wei Igaev, Maxim Joseph, Agnel P. Kihara, Daisuke Kumar, Dilip Mittal, Sumit Monastyrskyy, Bohdan Olek, Mateusz Palmer, Colin M. Patwardhan, Ardan Perez, Alberto Pfab, Jonas Pintilie, Grigore D. Richardson, Jane S. Rosenthal, Peter B. Sarkar, Daipayan Schäfer, Luisa U. Schmid, Michael F. Schröder, Gunnar F. Shekhar, Mrinal Si, Dong Singharoy, Abishek Terashi, Genki Terwilliger, Thomas C. Vaiana, Andrea Wang, Liguo Wang, Zhe Wankowicz, Stephanie A. Williams, Christopher J. Winn, Martyn Wu, Tianqi Yu, Xiaodi Zhang, Kaiming Berman, Helen M. Chiu, Wah Nat Methods Analysis This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density. Nature Publishing Group US 2021-02-04 2021 /pmc/articles/PMC7864804/ /pubmed/33542514 http://dx.doi.org/10.1038/s41592-020-01051-w Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Analysis
Lawson, Catherine L.
Kryshtafovych, Andriy
Adams, Paul D.
Afonine, Pavel V.
Baker, Matthew L.
Barad, Benjamin A.
Bond, Paul
Burnley, Tom
Cao, Renzhi
Cheng, Jianlin
Chojnowski, Grzegorz
Cowtan, Kevin
Dill, Ken A.
DiMaio, Frank
Farrell, Daniel P.
Fraser, James S.
Herzik, Mark A.
Hoh, Soon Wen
Hou, Jie
Hung, Li-Wei
Igaev, Maxim
Joseph, Agnel P.
Kihara, Daisuke
Kumar, Dilip
Mittal, Sumit
Monastyrskyy, Bohdan
Olek, Mateusz
Palmer, Colin M.
Patwardhan, Ardan
Perez, Alberto
Pfab, Jonas
Pintilie, Grigore D.
Richardson, Jane S.
Rosenthal, Peter B.
Sarkar, Daipayan
Schäfer, Luisa U.
Schmid, Michael F.
Schröder, Gunnar F.
Shekhar, Mrinal
Si, Dong
Singharoy, Abishek
Terashi, Genki
Terwilliger, Thomas C.
Vaiana, Andrea
Wang, Liguo
Wang, Zhe
Wankowicz, Stephanie A.
Williams, Christopher J.
Winn, Martyn
Wu, Tianqi
Yu, Xiaodi
Zhang, Kaiming
Berman, Helen M.
Chiu, Wah
Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge
title Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge
title_full Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge
title_fullStr Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge
title_full_unstemmed Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge
title_short Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge
title_sort cryo-em model validation recommendations based on outcomes of the 2019 emdataresource challenge
topic Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864804/
https://www.ncbi.nlm.nih.gov/pubmed/33542514
http://dx.doi.org/10.1038/s41592-020-01051-w
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